This analysis estimates the impact of Balto usage on Outbound transfer rate for SelectQuote agents. To estimate this impact, the following process is used:
We employ this approach to account for all potential confounding factors linked to the KPI of interest that could bias results in the presence of insufficient group randomization. Taking this approach also avoids unnecessary aggregations and maximizes available information to make statistical inference.
We find a positive statistically significant effect for Dual Skilled agents, and a statistically insignificant negative effect for Specialty agents.
| Transfer Rate | ||
|---|---|---|
| Predictors | Odds Ratios | 95% CI |
| Intercept | 0.01 *** | 0.00 – 0.01 |
| Balto User = Yes | 2.57 * | 0.94 – 6.99 |
| Agent Level = Specialty | 3.35 ** | 1.05 – 10.75 |
|
Balto User = Yes * Agent Level = Specialty |
0.39 | 0.11 – 1.34 |
| Linear Time Trend | 0.76 *** | 0.64 – 0.91 |
| Random Effects | ||
| σ2 | 3.29 | |
| τ00 Agent | 0.00 | |
| τ00 VendorCampaignName | 0.00 | |
| N VendorCampaignName | 18 | |
| N Agent | 28 | |
| AIC | 1485.773 | |
| log-Likelihood | -735.887 | |
|
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